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Statement of Problem Each science domain or community develops its own terminology to describe concepts, resources (objects, data) and relationships Data discovery and data sharing depend critically on being able to attach unambiguous meaning to the terms used to describe domain knowledge Generalized metadata standards such as ISO 19115 lack domain-specific elements

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Ontologies Expressed in a formal conceptual language (UML, ERD, RDF, OWL,...) where symbols, text and rules of grammar are used to express –classes (conceptualizations of objects) –instances of classes –properties of classes –relationships between classes

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The Big Question Who is going to do it? –DIS subcommittee of domain experts How will it be funded? –Corporate underwriting? –Prototype

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Process There is no one correct way to model a domain— there are always viable alternatives. Ontology development is necessarily an iterative process.

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Approaches – Top Down Begin with survey of existing domain knowledge representations in each IPY discipline –Reuse –Many to choose from –Investigate tools for bringing these knowledge bases into a common system

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Approaches – Bottom Up System for assigning subject metadata (tagging) –High level terms from defined domain specification –Leave discovery and simple semantic relationships to web services such as Google –Mechanism for distilling subject metadata once assigned –Once data released, users should be able to assign new tags –Community review and editing (wiki?)

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Outcome Legacy of IPY will be a dynamic system for cross-domain information discovery and retrieval –Community based –Language neutral